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CSRD & ESG Data Extractor API (Scope 1, 2, 3)

Automate the extraction of sustainability metrics from complex Annual Reports (PDF & HTML). Designed for ESG Consultants, Carbon Accounting Platforms, and Financial Analysts.

🚀 Why use this Actor?

With the CSRD (Corporate Sustainability Reporting Directive) deadline approaching, extracting data manually from 200+ page PDF reports is slow, expensive, and error-prone.

This Actor is an enterprise-grade extraction engine that navigates corporate websites, downloads Sustainability/Annual Reports, and uses AI to extract structured Scope 1, 2, and 3 emissions data with high precision.

Key Features

• 📄 Advanced PDF Parsing: Unlike simple HTML scrapers, this actor downloads and processes heavy PDF files (OCR capabilities included for scanned tables).
• 🛡️ Anti-Blocking Technology: Built on top of Puppeteer with Residential Proxies and stealth plugins to bypass Cloudflare and strict corporate firewalls.
• 🎯 Scope 1, 2, 3 Granularity: Extracts specific emission figures, units (tCO2e), and reporting years.
• 🔍 Audit Trail & Citations: Every extracted data point includes the source context (text snippet or page reference) so you can verify the numbers for compliance.
• 📊 Reliability Scoring: Returns a confidence score and reasoning for every extraction, flagging potential data gaps.

🛠️ How it works

1. Input: You provide the domain (e.g., volvocars.com) and the company_name.
2. Discovery: The actor scans the website to find the latest "Sustainability Report", "Non-Financial Statement", or "Annual Report".
3. Processing: It downloads the document (handling PDF or HTML).
4. Extraction: Using LLM-powered analysis, it identifies ESG tables and relevant paragraphs.
5. Output: You receive a clean JSON with the structured data.

📥 Input Parameters

The input of this actor should be JSON.

Example Input

{
"domain":"volvocars.com",
"company_name":"Volvo Car Corporation",
"reporting_year":"2023",
"force_scrape":true
}

📤 Output Example

The results are stored in the default dataset associated with the run. Note how the actor distinguishes between market-based Scope 2 and the massive Scope 3 categories typical of automotive companies.

[
{
"domain":"volvocars.com",
"company_name":"Volvo Car Corporation",
"reporting_year":2023,
"status":"success",
"data":{
"emissions":{
"scope_1":{
"value":38000,
"unit":"tCO2e",
"context":"Direct GHG emissions from manufacturing and operations (Page 182, Sustainability Notes)",
"confidence":"High"
},
"scope_2":{
"value":12000,
"type":"market-based",
"unit":"tCO2e",
"context":"Indirect emissions from purchased electricity, heating and cooling (market-based). Location-based was 85,000 tCO2e.",
"confidence":"High"
},
"scope_3":{
"value":42500000,
"unit":"tCO2e",
"categories_included":["Purchased goods and services","Use of sold products","Upstream transportation"],
"confidence":"High",
"notes":"Includes lifecycle emissions from sold vehicles."
}
},
"reliability_score":0.98,
"reliability_reasoning":"Data extracted explicitly from the 'GRI Content Index' and 'Greenhouse Gas Emissions' tables in the Annual Report 2023."
},
"source_url":"https://investors.volvocars.com/annual-report-2023.pdf",
"scraped_at":"2024-05-20T14:30:00Z"
}
]

💰 Pricing & Cost Efficiency

This actor is designed to be significantly cheaper than manual data entry.

• Manual Entry: An analyst takes ~30-60 minutes to find and transcribe Scope 1-3 data per report. Cost: ~$50/report (labor).
• Apify Actor: Takes ~1-3 minutes. Cost: Fraction of manual labor.

Recommended for bulk usage. If you need to process 100+ companies, please contact me via the Issues tab for a custom solution.

⚠️ Known Limitations

• Scanned PDFs: While OCR is supported, extremely low-quality scans (images of text without a text layer) may result in lower confidence scores.
• Language: Currently optimized for English and Italian reports. Support for German, French, and Spanish is in beta.

Support & Feedback

If you encounter any issues, have feature requests, or need a custom integration for your enterprise pipeline, please create an issue in the tab above.